What you need to know about vision sensors and their applications

The benefits of vision sensing are starting to be realised as a true asset when it comes to manufacturing, testing and quality assurance. Machine vision sensing is area that SICK excel in and many users are experiencing the true value that SICK, the leading sensor supplier are bringing to industry. We met up with them recently to find out more about this technology and its applications.

Within manufacturing and industrial processing, vision inspection is becoming a key ingredient of the movement and realisation of the benefits associated with the Internet of Things. Smart vision inspection devices will be able to analyse from a pre-defined reference source and determine whether something passes or fails, simply by recognising the defined attributes, but this is only the basics.

In the video below Neil describes applications for the SICK Inspector i 40 (123-5181) within the food and beverage industry, and also how cars are actually glued together in the automotive industry.

Vision inspection - opening new realms of possibilities...

Vision sensing is entering new realms and it’s not just heavy industry that’s taking the giant steps towards greater control and productivity. Many in the Agricultural industry are starting to adopt smart vision sensing to ensure that crops are returning greater yields. No longer will the farmer need to tend to his crop.

Small smart machines (no bigger than a small car) are now being fitted with vision sensors that are able to determine the difference between crop and weeds. Using a reference source they are able to distinguish from multiple types of weed, thus allowing selection of the most effective herbicide. With pinpoint accuracy, this is sprayed directly on to the weed leaf or stem, thus protecting the plant and killing the weed.

During harvest most farmers suffer from something known as slaughter harvesting, this when a farmer harvests an entire field at a time, only to discover that some of the crop doesn’t meet the requirements in terms of size as demanded by supermarkets. Up to 25% can be thrown away as substandard. With small smart machines, a phased approach can be used to harvest. Instead of performing a full harvest of the field, the machine will only harvest against the stored reference source within the smart camera (vision inspection device). If the crop is not ripe it will recognise this, and delay the harvest. It will only harvest when the product matches the pre-defined attributes, for example, the size demanded by the supermarkets. With this method, selected harvesting becomes the norm and more efficiency is returned and less produce is wasted. Moving this forward, these small smart machines may be able to provide, selectively, the nutrients required to ensure the crop is given the best possible chance of returning a 100% yield.

Favourite things are Family, Music, Judo and Game of Thrones. Also I have the ability to retain and quote useless facts, something that pleases me but can annoy others. My engineering hero - Isambard Kingdom Brunel